Diagnosis of the Nutritional Status of Garlic Crops

• Autor(a) principal: Cunha,Mário Lúcio Pereira
• Data de Publicação: 2016
• Outros Autores: Aquino,Leonardo Angelo, Novais,Roberto Ferreira, Clemente,Junia Maria, and,Priscila Maria de Aquino, Oliveira,Thaisa Fernanda
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Ciência do Solo (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100502
• topic: nutritional balance; diagnostic indexes; Allium sativum L

ABSTRACT Univariate methods for diagnosing nutritional status such as the sufficiency range and the critical level for garlic crops are very susceptible to the effects of dilution and accumulation of nutrients. Therefore, this study aimed to establish bivariate and multivariate norms for this crop using the Diagnosis and Recommendation Integrated System (DRIS) and Nutritional Composition Diagnosis (CND), respectively. The criteria used were nutritional status and the sufficiency range, and then the diagnoses were compared. The study was performed in the region of Alto Paranaíba, MG, Brazil, during the crop seasons 2012 and 2013. Samples comprised 99 commercial fields of garlic, cultivated with the cultivar “Ito” and mostly established in Latossolo Vermelho-Amarelo Distrófico (Oxisol). Copper and K were the nutrients with the highest number of fields diagnosed as limiting by lack (LF) and limiting by excess (LE), respectively. The DRIS method presented greater tendency to diagnose LF, while the CND tended towards LE. The sufficiency range of both methods presented narrow ranges in relation to those suggested by the literature. Moreover, all ranges produced by the CND method provided narrower ranges than the DRIS method. The CND method showed better performance than DRIS in distinguishing crop yield covered by different diagnoses. Turning to the criterion of evaluation, the study found that nutritional status gave a better performance than sufficiency range in terms of distinguishing diagnoses regarding yield.